Crystal Plasticity Modeling and Experimental Validation with an Orientation Distribution Function for Ti-7Al Alloy

Abstract

An orientation distribution function based model is used for micromechanical modeling of the titanium-aluminum alloys, Ti-0 wt % Al and Ti-7 wt % Al, which are in demand for many aerospace applications. This probability descriptor based modeling approach is different than crystal plasticity finite element techniques since it computes the averaged material properties using upper bound averaging. A rate-independent single-crystal plasticity model is implemented to compute the effect of macroscopic strain on the polycrystal. An optimization problem is defined for calibrating the basal, prismatic, pyramidal slip system and twin parameters using the available tension and compression experimental data. The crystal plasticity parameters of Ti-7 wt % Al are not studied extensively in literature, and therefore the optimization results for the crystal plasticity model realization produce unique data, which will be beneficial to future studies in the field. The sensitivities of the slip and twin parameters to the design objectives are also investigated to identify the most critical slip system parameters. Using the optimum design parameters, the microstructural textures, during the tension test, are predicted by the crystal plasticity finite element simulations, and compared to the available experimental texture and scanning electron microscope-digital image correlation data.

Do Epistemic Uncertainties Allow for Replacing Microstructural Experiments with Reconstruction Algorithms?

“…The material properties of interest in this application are not only the stiffness parameters but also the yield stress values at different strain offsets because the yield stress is more sensitive to the microstructural uncertainties. The property matrices for stiffness and yield stress values are obtained using the single crystal values presented in our previous work [34]. The probability distributions of the material properties computed using the MRF samples can also be compared with the experimental values.…”

PRISMS: An Integrated, Open-Source Framework for Accelerating Predictive Structural Materials Science

“…The microstructural strain response predicted by the PRISMS-Plasticity CPFE module has been validated by comparison with strain maps from SEM-DIC measurements, and it provides a reliable indicator of stress heterogeneity within grains as well as Schmid factor variations due to the effect of neighbor grains. 65,66 The crystal plasticity code has been used for computation of dislocation density distribution for use in static recrystallization models 67 and for initializing the single crystal parameters of other alloys (Ti, Al, Fe) [68][69][70] in projects outside the PRISMS Center.…”

Reduced-Order Modeling Approach for Materials Design with a Sequence of Processes

“…Finite element discretization of the orientation space and associated integration schemes using Gauss quadrature allows the matrix representation of Eq. (1) [2][3][4][5][6][7][8][9][10]. The ODF is discretized into N independent nodes with N elem finite elements and N int integration points per element.…”

“…Using this parametrization, any polycrystal property can be expressed in a linear form [19]. The readers are referred to recent works by the authors [2-6,9] and Acar et al [7,8,10] for more information about microstructural modeling.…”

“…In this work, the ODF values are parameterized using a Rodrigues representation. The computational microstructural modeling has been studied extensively in the earlier works of Acar and Sundararaghavan [2][3][4][5][6], Acar et al [7,8], Acar and Sundararaghavan [9], Acar et al [10], and other works in the literature [11][12][13][14][15] by using different computational techniques. The design of microstructures has also been exercised by Acar and Sundararaghavan [2][3][4] and Acar et al [7,8] using the ODF model and a linear solution scheme to achieve optimum material properties.…”